Biomedical subjects

Pierre Bruneau

Publications and source records attributed to Pierre Bruneau.

4 recordsLinked to original sources

PubMed2006

Can we estimate the accuracy of ADME-Tox predictions?

There have recently been developments in the methods used to access the accuracy of the prediction and applicability domain of absorption, distribution, metabolism, excretion and toxicity models, and also in the methods used to predict the physicochemical properties of compounds in the early stages of drug development. The methods are classified into two main groups: those based on the analysis of similarity of molecules, and those based on the analysis of calculated properties. An analysis of octanol-water distribution coefficients is used to exemplify the consistency of estimated and calculated accuracy of the ALOGPS program (http://www.vcclab.org) to predict in-house and publicly available datasets.

Algorithms↗

PubMed2004

Application of ALOGPS to predict 1-octanol/water distribution coefficients, logP, and logD, of AstraZeneca in-house database.

The ALOGPS 2.1 was developed to predict 1-octanol/water partition coefficients, logP, and aqueous solubility of neutral compounds. An exclusive feature of this program is its ability to incorporate new user-provided data by means of self-learning properties of Associative Neural Networks. Using this feature, it calculated a similar performance, RMSE = 0.7 and mean average error 0.5, for 2569 neutral logP, and 8122 pH-dependent logD(7.4), distribution coefficients from the AstraZeneca "in-house" database. The high performance of the program for the logD(7.4) prediction looks surprising, because this property also depends on ionization constants pKa. Therefore, logD(7.4) is considered to be more difficult to predict than its neutral analog. We explain and illustrate this result and, moreover, discuss a possible application of the approach to calculate other pharmacokinetic and biological activities of chemicals important for drug development.

1-Octanol↗

PubMed2002

Rational determination of transfer free energies of small drugs across the water-oil interface.

The application of statistical simulations to the estimation of transfer free energies of pharmacologically relevant organic molecules is reported. Large-scale molecular dynamics simulations have been carried out on a series of four solutes, viz. antipyrine, caffeine, ganciclovir, and alpha-D-glucose, at the water-dodecane interface as a model of a biological water-membrane interfacial system. Agreement with experimentally determined partition coefficients is remarkable, demonstrating that free energy calculations, when executed with appropriate protocols, have reached the maturity to predict thermodynamic quantities of interest to the pharmaceutical world. The computational effort that warrants accurate, converged free energies remains, however, in large measure, incompatible with the high-throughput exploration of large sets of pharmacologically active drugs sought by industrial settings. Compared to the cost-effective, fast estimation of simple partition coefficients, the present free energy calculations, nevertheless, offer a far more detailed information about the underlying energetics of the system when the solute is translocated across the water-dodecane interface, which can be valuable in the context of de novo drug design.

Alkanes↗

PubMedDate not supplied

logD7.4 modeling using Bayesian Regularized Neural Networks. Assessment and correction of the errors of prediction.

Bayesian Regularized Neural Networks (BRNNs) employing Automatic Relevance Determination (ARD) are used to construct a predictive model for the distribution coefficient logD7.4 from an in-house data set of 5000 compounds with experimental endpoints. A method for assessing the accuracy of prediction is established based upon a query compound's distance to the training set. logD7.4 predictions are also dynamically corrected with an associated library of compounds of continuously updated, experimentally measured logD7.4 values. A comparison of local models and associated libraries comprising separate ionization class subsets of compounds to compounds of a homogeneous ionization class reveals in this case that local models and libraries have no advantage over global models and libraries.

Algorithms↗